A Simple and Strong Baseline: NAIST-NICT Neural Machine Translation System for WAT2017 English-Japanese Translation Task
Yusuke Oda, Katsuhito Sudoh, Satoshi Nakamura, Masao Utiyama, Eiichiro Sumita
Abstract
This paper describes the details about the NAIST-NICT machine translation system for WAT2017 English-Japanese Scientific Paper Translation Task. The system consists of a language-independent tokenizer and an attentional encoder-decoder style neural machine translation model. According to the official results, our system achieves higher translation accuracy than any systems submitted previous campaigns despite simple model architecture.- Anthology ID:
- W17-5712
- Volume:
- Proceedings of the 4th Workshop on Asian Translation (WAT2017)
- Month:
- November
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Toshiaki Nakazawa, Isao Goto
- Venue:
- WAT
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 135–139
- Language:
- URL:
- https://aclanthology.org/W17-5712
- DOI:
- Cite (ACL):
- Yusuke Oda, Katsuhito Sudoh, Satoshi Nakamura, Masao Utiyama, and Eiichiro Sumita. 2017. A Simple and Strong Baseline: NAIST-NICT Neural Machine Translation System for WAT2017 English-Japanese Translation Task. In Proceedings of the 4th Workshop on Asian Translation (WAT2017), pages 135–139, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- A Simple and Strong Baseline: NAIST-NICT Neural Machine Translation System for WAT2017 English-Japanese Translation Task (Oda et al., WAT 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W17-5712.pdf